2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA)最新文献_第2页

Illuminant estimation error detection for outdoor scenes using transformers 基于变压器的室外场景光源估计误差检测

2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA) Pub Date : 2021-09-13 DOI: 10.1109/ISPA52656.2021.9552045

Donik Vršnak, Ilija Domislović, M. Subašić, S. Lončarić

引用次数: 1

Significance of Morphological Features in Rice Variety Classification Using Hyperspectral Imaging 形态特征在水稻品种分类中的高光谱成像意义

2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA) Pub Date : 2021-09-13 DOI: 10.1109/ISPA52656.2021.9552086

V. Filipović, Marko Neven Panić, S. Brdar, Branko Brkljac

引用次数: 2

Robust Deep Simple Online Real-Time Tracking 鲁棒深度简单在线实时跟踪

2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA) Pub Date : 2021-09-13 DOI: 10.1109/ISPA52656.2021.9552062

Abdelbadie Belmouhcine, J. Simon, L. Courtrai, S. Lefèvre

{"title":"Robust Deep Simple Online Real-Time Tracking","authors":"Abdelbadie Belmouhcine, J. Simon, L. Courtrai, S. Lefèvre","doi":"10.1109/ISPA52656.2021.9552062","DOIUrl":"https://doi.org/10.1109/ISPA52656.2021.9552062","url":null,"abstract":"Simple Online and Real-time Tracking (SORT) and its deep extension (DeepSORT) are simple, fast, and effective multi-object tracking by detection frameworks. Their main strengths are simplicity and speed. However, they still suffer from some problems, such as identity switch, instance merge, and many false positives, which prevent the tracking results from being used for subsequent tasks such as counting. In this paper, we strengthen and improve the tracking using EfficientDet and DeepSORT. In our approach, the motion prediction uses appearance, and the appearance embedding uses location. First, we modify the deep detection network to predict the objects' motion in the next frame by leveraging the attention between the current image and the next image. Second, an appearance-based metric is used to associate detection to tracks after false negatives and occlusion. This metric is a learned Mahalanobis distance between two feature descriptors constructed using EfficientDet and attention given to regions of interest from their images. Finally, we count only high confidence tracks having a minimum frequency of apparition. Our approach has been applied to a challenging real-life problem, namely seabed species tracking and counting. Our experimental results show that Robust DeepSORT reduces identity switches and merges. Thus, it improves tracking and counting evaluation measures while keeping the simplicity of the origlnal DeepSORT.","PeriodicalId":131088,"journal":{"name":"2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132118167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Semantic-Aware Environment Perception for Mobile Human-Robot Interaction 面向移动人机交互的语义感知环境感知

2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA) Pub Date : 2021-09-13 DOI: 10.1109/ISPA52656.2021.9552148

Thorsten Hempel, Marc-André Fiedler, Aly Khalifa, A. Al-Hamadi, Laslo Dinges

引用次数: 0

Automated Sex Assessment of Individual Adult Tooth X-Ray Images 成人牙齿x光图像的自动性别评估

2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA) Pub Date : 2021-09-13 DOI: 10.1109/ISPA52656.2021.9552124

D. Milošević, M. Vodanović, I. Galić, M. Subašić

{"title":"Automated Sex Assessment of Individual Adult Tooth X-Ray Images","authors":"D. Milošević, M. Vodanović, I. Galić, M. Subašić","doi":"10.1109/ISPA52656.2021.9552124","DOIUrl":"https://doi.org/10.1109/ISPA52656.2021.9552124","url":null,"abstract":"Sex assessment is an important step of the forensic process. Dental remains are often the only remains left to examine due to their resistance to decay and external factors. Contemporary forensic odontology literature describes multiple methods for sex assessment from mandibular parameters, all of which require manual measurements and expert training. This study aims to explore the applicability of deep learning and image analysis methods to automate this task, thus allowing for easier reproducibility of assessments, reduction of the time experts lose on repetitive tasks, and potentially better performance. We have evaluated state-of-the-art deep learning models and components on the largest dataset of individual adult tooth x-ray images, consisting of 76293 samples. This study also explores the usage of decayed or structurally altered teeth, with which contemporary methods struggle. Two types of models are constructed, a family of models specialized for specific tooth types, and a general model that can assess the sex from any tooth type. We examine the performance of those models per tooth type and age group, as well as the impact of decayed and structurally altered teeth. The specialized models achieve an overall accuracy of 72.40%, and the general model reaches an overall accuracy of 72.68%.","PeriodicalId":131088,"journal":{"name":"2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116391433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Proceedings of the 12th International Symposium on Image and Signal Processing and Analysis 第十二届图像与信号处理与分析国际研讨会论文集

2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA) Pub Date : 2021-09-13 DOI: 10.1109/ispa52656.2021.9552102

引用次数: 0

Approaches to Video Real time Multi-Object Tracking and Object Detection: A survey 视频实时多目标跟踪与目标检测方法综述

2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA) Pub Date : 2021-09-13 DOI: 10.1109/ISPA52656.2021.9552095

Sara Bouraya, A. Belangour

{"title":"Approaches to Video Real time Multi-Object Tracking and Object Detection: A survey","authors":"Sara Bouraya, A. Belangour","doi":"10.1109/ISPA52656.2021.9552095","DOIUrl":"https://doi.org/10.1109/ISPA52656.2021.9552095","url":null,"abstract":"The world is living a major shift from information era to artificial intelligence (AI) era. Machines are giving the ability to sense the surrounding world and to take decisions. Computer vision and especially multi-object tracking(MOT), which relies on Deep Learning, is at the heart of this shift. Indeed, with the growth of deep learning, the methods and algorithms that are tackling this problem have gained better performance from the integration of deep learning models. Deep Learning has been demonstrated as MOT, which tackles the challenges of in-and-out objects, unlabeled data, confusing appearance and occlusion. Deep learning, which relied on MOT techniques, has recently gained a fast ground from representation learning to modelling the networks thanks to the advancement of deep learning hypothesis and benchmark arrangement. This paper sums up and analyzes deep learning based MOT techniques which are at a highest level. The paper also offers a comprehensive review about the different techniques applied in MOT of deep learning based on different methods. Furthermore, this study analyzes the benefits and the constraints of current strategies, techniques and methods.","PeriodicalId":131088,"journal":{"name":"2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127580251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Spectral Bandwidth Recovery of Optical Coherence Tomography Images using Deep Learning 基于深度学习的光学相干层析成像光谱带宽恢复

2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA) Pub Date : 2021-09-13 DOI: 10.1109/ISPA52656.2021.9552122

T. Yu, Da Ma, Jayden Cole, M. Ju, M. Beg, M. Sarunic

{"title":"Spectral Bandwidth Recovery of Optical Coherence Tomography Images using Deep Learning","authors":"T. Yu, Da Ma, Jayden Cole, M. Ju, M. Beg, M. Sarunic","doi":"10.1109/ISPA52656.2021.9552122","DOIUrl":"https://doi.org/10.1109/ISPA52656.2021.9552122","url":null,"abstract":"Optical coherence tomography (OCT) is a noninvasive imaging modality utilized by ophthalmologists to acquire volumetric data to characterize the retina, the light-sensitive tissue at the back of the eye. OCT captures cross-sectional data and is used for the screening, monitoring, and treatment planning of retinal diseases. Technological developments to increase the speed of acquisition often results in systems with narrower spectral bandwidth, and hence a lower axial resolution. Traditionally, image-processing-based techniques have been utilized to reconstruct subsampled OCT data and more recently, deep-learning-based methods have been explored. In this study, we simulate reduced axial scan (A-scan) resolution by Gaussian windowing in the spectral domain and investigate the use of a learning-based approach for image feature reconstruction. Our experiment is limited by the size of our current dataset, and we leverage techniques like transfer learning from large natural image databases and image augmentation in our implementation. In anticipation of the reduced resolution that accompanies wide-field OCT systems, we attempt to reconstruct lost features using a pixel-to-pixel approach with an altered super-resolution GAN (SRGAN) architecture. Similar techniques have been used to upscale images of lower image size and resolution in medical images like radiographs. We build upon methods of super-resolution to explore methods of better aiding clinicians in their decision-making to improve patient outcomes.","PeriodicalId":131088,"journal":{"name":"2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134315378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Multilevel Subsampling of Principal Component Projections for Adaptive Compressive Sensing 自适应压缩感知中主成分投影的多水平子采样

2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA) Pub Date : 2021-09-13 DOI: 10.1109/ISPA52656.2021.9552127

Tin Vlašić, D. Seršić

引用次数: 0

Acoustic Features for Deep Learning-Based Models for Emergency Siren Detection: An Evaluation Study 基于深度学习的紧急警笛检测模型声学特征评价研究

2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA) Pub Date : 2021-09-13 DOI: 10.1109/ISPA52656.2021.9552140

Michela Cantarini, Anna Brocanelli, L. Gabrielli, S. Squartini

{"title":"Acoustic Features for Deep Learning-Based Models for Emergency Siren Detection: An Evaluation Study","authors":"Michela Cantarini, Anna Brocanelli, L. Gabrielli, S. Squartini","doi":"10.1109/ISPA52656.2021.9552140","DOIUrl":"https://doi.org/10.1109/ISPA52656.2021.9552140","url":null,"abstract":"Emergency Siren Detection is a topic of great importance for road safety. Nowadays, the design of cars with every comfort has improved the quality of driving, but distractions have also increased. Hence the usefulness of implementing an Emergency Vehicle Detection System: if installed inside the car, it alerts the driver of its approach, and if installed outdoors in strategic locations, it automatically activates reserved lanes. In this paper, we perform Emergency Siren Detection with a Convolutional Neural Network-based deep learning model. We investigate acoustic features to propose a low computational cost algorithm. We employ Short-Time Fourier Transform spectrograms as features and improve the classification performance by applying a harmonic percussive source separation technique. The enhancement of the harmonic components of the spectrograms gives better results than more computationally complex features. We also demonstrate the relevance of the siren harmonic contents in the classification task. The reduction of the network hyperparameters decreases the computational load of the algorithm and facilitates its implementation in real-time embedded systems.","PeriodicalId":131088,"journal":{"name":"2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115850262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5